Create app.py

app.py

@@ -0,0 +1,25 @@
+import torch
+import gradio as gr
+from transformers import pipeline
+
+# Load summarization pipeline
+text_summary = pipeline(
+    "summarization",
+    model="sshleifer/distilbart-cnn-12-6",
+    torch_dtype=torch.float32   # CPU stable
+)
+
+def summary(input_text):
+    result = text_summary(input_text)
+    return result[0]['summary_text']
+
+# Gradio app
+demo = gr.Interface(
+    fn=summary,
+    inputs=[gr.Textbox(label="Input text to summarize", lines=6)],
+    outputs=[gr.Textbox(label="Summarized text", lines=4)],
+    title="@GenAILearniverse Project 1: Text Summarizer",
+    description="This application summarizes long text into short and meaningful summaries."
+)
+
+demo.launch()